langgraph-workflows

You can create a declarative LangGraph workflow by defining nodes and edges with conditional routing using the StateGraph API to orchestrate stateful execution. This approach allows you to model linear, branching, and looping graphs.

The best way to orchestrate multi-agent coordination in LangGraph is by routing between different node handlers using the StateGraph API. This declarative method manages stateful execution and enables dynamic decision paths across agents.

Yes, you can build looping and fan-in/fan-out patterns in LangGraph workflows to handle iterative processes and parallelism. The StateGraph API supports these declarative structures alongside branching for dynamic execution.

Yes, you need Python and the LangGraph library to define and execute stateful node graphs using the StateGraph API. It provides the necessary START and END constants to model declarative execution paths.

Declarative stateful node execution in LangGraph requires Python and the LangGraph library to model graphs. While it supports branching and looping, you must explicitly define START and END constants and node handlers to manage execution correctly.